Conditioned source separations have attracted significant attention because of their flexibility, applicability and extensionality. Their performance was usually inferior to the existing approaches, such as the single source separation model. However, a recently proposed method called LaSAFT-Net has shown that conditioned models can show comparable performance against existing single-source separation models. This paper presents LightSAFT-Net, a lightweight version of LaSAFT-Net. As a baseline, it provided a sufficient SDR performance for comparison during the Music Demixing Challenge at ISMIR 2021. This paper also enhances the existing LightSAFT-Net by replacing the LightSAFT blocks in the encoder with TFC-TDF blocks. Our enhanced LightSAFT-Net outperforms the previous one with fewer parameters.Conditioned source separations have attracted significant attention because of their flexibility, applicability and extensionality. Their performance was usually inferior to the existing approaches, such as the single source separation model. However, a recently proposed method called LaSAFT-Net has shown that conditioned models can show comparable performance against existing single-source separation models. This paper presents LightSAFT-Net, a lightweight version of LaSAFT-Net. As a baseline, it provided a sufficient SDR performance for comparison during the Music Demixing Challenge at ISMIR 2021.
翻译：限定源的分离因其灵活性、可适用性和扩展性而引起极大关注,其性能通常低于现有方法,例如单一源分离模型;然而,最近提出的一个名为LaSAFT-Net 的方法表明,有条件的模型能够显示与现有单一源分离模型的类似性能。本文展示了LaSAFT-Net的轻量级版本LASAFT-Net。作为一个基线,它提供了足够的特别提款权性能,以便在IMIR 2021的音乐分解挑战期间进行比较。本文还介绍了现有 LightSAFT-Net 的功能,用TFC-TDF 区块取代了编码中 LightSAFT-Net 区块。我们增强的LightSAFT-Net 的功能比前一个参数要短。由于具有灵活性、可适用性和扩展性能,因此引起极大关注。作为基准,其性能通常低于现有方法,如单一源分离模型。然而,最近提出的一种称为LSAFT-Net的方法表明,有条件的模型可以显示与现有的单一源分离模型的类似性性能。本文介绍了在IFT-FT-Net期间对IFSA 20号进行充分的业绩比较。
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